Can the NVIDIA RTX 3070 run Qwen3 32B?

RTX 3070 × Qwen3 32B8K context
NoDoes not fit in memory
Memory at Q4_K_M22.6 GB of 8 GB
Weights 19.9 GBKV cache 2.1 GBRuntime 0.6 GB
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

No. Even at Q4_K_M, Qwen3 32B needs about 22.6 GB, but the NVIDIA RTX 3070 has 8 GB usable. You could offload some layers to system RAM, but it will be very slow.

Run it on a rented GPU

On a cloud GPU with enough memory, the same command you'd use locally works:

ollama run qwen3:32b

At Q4_K_M it needs about 22.6 GB, so pick a GPU with at least 24 GB.

Run it in the cloud

Too big for the NVIDIA RTX 3070? Run Qwen3 32B on a rented GPU instead.

Rent a cloud GPU by the hour. No upfront cost, stop any time.

Memory needed by quantization

At 8,192 tokens of context. The black line marks the 8 GB the NVIDIA RTX 3070 can use.

QuantQualityMemoryFits?Speed
FP16Full quality68.3 GBToo big—
Q8_0Near-lossless37.6 GBToo big—
Q6_KExcellent29.6 GBToo big—
Q5_K_MVery good26.1 GBToo big—
Q4_K_MGood, most popular22.6 GBToo big—
Q3_K_MNoticeably degraded18.8 GBToo big—
Q2_KHeavily degraded15 GBToo big—

Frequently asked questions

Can NVIDIA RTX 3070 run Qwen3 32B?

No. Even at Q4_K_M, Qwen3 32B needs about 22.6 GB, but the NVIDIA RTX 3070 has 8 GB usable. You could offload some layers to system RAM, but it will be very slow.

How much VRAM does Qwen3 32B need?

About 22.6 GB at Q4_K_M with 8,192 tokens of context, and about 68.3 GB at full FP16 precision.

How fast is Qwen3 32B on the NVIDIA RTX 3070?

It does not fit in the NVIDIA RTX 3070's memory, so most layers would run from system RAM and generation would be very slow.